Detection of aneuploidy in patients with cancer through amplification of long interspersed nucleotide elements (LINEs)

Genome-wide repeat landscapes in cancer and cell-free DNA

Genetic changes in repetitive sequences are a hallmark of cancer and other diseases, but characterizing these has been challenging using standard sequencing approaches. We developed a de novo kmer finding approach, called ARTEMIS (Analysis of RepeaT EleMents in dISease), to identify repeat elements from whole-genome sequencing. Using this method, we analyzed 1.2 billion kmers in 2837 tissue and plasma samples from 1975 patients, including those with lung, breast, colorectal, ovarian, liver, gastric, head and neck, bladder, cervical, thyroid, or prostate cancer. We identified tumor-specific changes in these patients in 1280 repeat element types from the LINE, SINE, LTR, transposable element, and human satellite families. These included changes to known repeats and 820 elements that were not previously known to be altered in human cancer. Repeat elements were enriched in regions of driver genes, and their representation was altered by structural changes and epigenetic states. Machine learning analyses of genome-wide repeat landscapes and fragmentation profiles in cfDNA detected patients with early-stage lung or liver cancer in cross-validated and externally validated cohorts. In addition, these repeat landscapes could be used to noninvasively identify the tissue of origin of tumors. These analyses reveal widespread changes in repeat landscapes of human cancers and provide an approach for their detection and characterization that could benefit early detection and disease monitoring of patients with cancer.

Aneuploidy Landscape in Precursors of Ovarian Cancer

PURPOSE

Serous tubal intraepithelial carcinoma (STIC) is now recognized as the main precursor of ovarian high-grade serous carcinoma (HGSC). Other potential tubal lesions include p53 signatures and tubal intraepithelial lesions. We aimed to investigate the extent and pattern of aneuploidy in these epithelial lesions and HGSC to define the features that characterize stages of tumor initiation and progression.

EXPERIMENTAL DESIGN

We applied RealSeqS to compare genome-wide aneuploidy patterns among the precursors, HGSC (cases, n = 85), and histologically unremarkable fallopian tube epithelium (HU-FTE; control, n = 65). On the basis of a discovery set (n = 67), we developed an aneuploidy-based algorithm, REAL-FAST (Repetitive Element AneupLoidy Sequencing Fallopian Tube Aneuploidy in STIC), to correlate the molecular data with pathology diagnoses. We validated the result in an independent validation set (n = 83) to determine its performance. We correlated the molecularly defined precursor subgroups with proliferative activity and histology.

RESULTS

We found that nearly all p53 signatures lost the entire Chr17, offering a "two-hit" mechanism involving both TP53 and BRCA1 in BRCA1 germline mutation carriers. Proliferatively active STICs harbor gains of 19q12 (CCNE1), 19q13.2, 8q24 (MYC), or 8q arm, whereas proliferatively dormant STICs show 22q loss. REAL-FAST classified HU-FTE and STICs into 5 clusters and identified a STIC subgroup harboring unique aneuploidy that is associated with increased proliferation and discohesive growth. On the basis of a validation set, REAL-FAST showed 95.8% sensitivity and 97.1% specificity in detecting STIC/HGSC.

CONCLUSIONS

Morphologically similar STICs are molecularly distinct. The REAL-FAST assay identifies a potentially "aggressive" STIC subgroup harboring unique DNA aneuploidy that is associated with increased cellular proliferation and discohesive growth. REAL-FAST offers a highly reproducible adjunct technique to assist the diagnosis of STIC lesions.

Machine learning to detect the SINEs of cancer

We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a machine learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to 7615 samples from 5178 individuals, 2073 with solid cancer and the remainder without cancer. Samples from patients with cancer and controls were prespecified into four cohorts used for model training, analyte integration, and threshold determination, validation, and reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the validation cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and eight common protein biomarkers detected 51% of the cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature-the global reduction of AluS subfamily elements in the circulating DNA of patients with solid cancer. We confirmed this reduction through the analysis of another independent dataset obtained with a different approach (whole-genome sequencing). The evaluation of Alu elements may therefore have the potential to enhance the performance of several methods designed for the earlier detection of cancer.

Liquid biopsy biomarkers to guide immunotherapy in breast cancer

Immune checkpoint inhibitors (ICIs) therapy has emerged as a promising treatment strategy for breast cancer (BC). However, current reliance on immunohistochemical (IHC) detection of PD-L1 expression alone has limited predictive capability, resulting in suboptimal efficacy of ICIs for some BC patients. Hence, developing novel predictive biomarkers is indispensable to enhance patient selection for immunotherapy. In this context, utilizing liquid biopsy (LB) can provide supplementary or alternative value to PD-L1 IHC testing for identifying patients most likely to benefit from immunotherapy and exhibit favorable responses. This review discusses the predictive and prognostic value of LB in breast cancer immunotherapy, as well as its limitations and future directions. We aim to promote the individualization and precision of immunotherapy in BC by elucidating the role of LB in clinical practice.

The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer

Cell-free DNA (cfDNA) concentrations from patients with cancer are often elevated compared with those of healthy controls, but the sources of this extra cfDNA have never been determined. To address this issue, we assessed cfDNA methylation patterns in 178 patients with cancers of the colon, pancreas, lung, or ovary and 64 patients without cancer. Eighty-three of these individuals had cfDNA concentrations much greater than those generally observed in healthy subjects. The major contributor of cfDNA in all samples was leukocytes, accounting for ∼76% of cfDNA, with neutrophils predominating. This was true regardless of whether the samples were derived from patients with cancer or the total plasma cfDNA concentration. High levels of cfDNA observed in patients with cancer did not come from either neoplastic cells or surrounding normal epithelial cells from the tumor's tissue of origin. These data suggest that cancers may have a systemic effect on cell turnover or DNA clearance.

SIGNIFICANCE

The origin of excess cfDNA in patients with cancer is unknown. Using cfDNA methylation patterns, we determined that neither the tumor nor the surrounding normal tissue contributes this excess cfDNA-rather it comes from leukocytes. This finding suggests that cancers have a systemic impact on cell turnover or DNA clearance. See related commentary by Thierry and Pisareva, p. 2122. This article is featured in Selected Articles from This Issue, p. 2109.

Seq-ing the SINEs of central nervous system tumors in cerebrospinal fluid

It is often challenging to distinguish cancerous from non-cancerous lesions in the brain using conventional diagnostic approaches. We introduce an analytic technique called Real-CSF (repetitive element aneuploidy sequencing in CSF) to detect cancers of the central nervous system from evaluation of DNA in the cerebrospinal fluid (CSF). Short interspersed nuclear elements (SINEs) are PCR amplified with a single primer pair, and the PCR products are evaluated by next-generation sequencing. Real-CSF assesses genome-wide copy-number alterations as well as focal amplifications of selected oncogenes. Real-CSF was applied to 280 CSF samples and correctly identified 67% of 184 cancerous and 96% of 96 non-cancerous brain lesions. CSF analysis was considerably more sensitive than standard-of-care cytology and plasma cell-free DNA analysis in the same patients. Real-CSF therefore has the capacity to be used in combination with other clinical, radiologic, and laboratory-based data to inform the diagnosis and management of patients with suspected cancers of the brain.

Dynamics of Sequence and Structural Cell-Free DNA Landscapes in Small-Cell Lung Cancer

PURPOSE

Patients with small-cell lung cancer (SCLC) have an exceptionally poor prognosis, calling for improved real-time noninvasive biomarkers of therapeutic response.

EXPERIMENTAL DESIGN

We performed targeted error-correction sequencing on 171 serial plasmas and matched white blood cell (WBC) DNA from 33 patients with metastatic SCLC who received treatment with chemotherapy (n = 16) or immunotherapy-containing (n = 17) regimens. Tumor-derived sequence alterations and plasma aneuploidy were evaluated serially and combined to assess changes in total cell-free tumor load (cfTL). Longitudinal dynamic changes in cfTL were monitored to determine circulating cell-free tumor DNA (ctDNA) molecular response during therapy.

RESULTS

Combined tiered analyses of tumor-derived sequence alterations and plasma aneuploidy allowed for the assessment of ctDNA molecular response in all patients. Patients classified as molecular responders (n = 9) displayed sustained elimination of cfTL to undetectable levels. For 14 patients, we observed initial molecular responses, followed by ctDNA recrudescence. A subset of patients (n = 10) displayed a clear pattern of molecular progression, with persistence of cfTL across all time points. Molecular responses captured the therapeutic effect and long-term clinical outcomes in a more accurate and rapid manner compared with radiographic imaging. Patients with sustained molecular responses had longer overall (log-rank P = 0.0006) and progression-free (log-rank P < 0.0001) survival, with molecular responses detected on average 4 weeks earlier than imaging.

CONCLUSIONS

ctDNA analyses provide a precise approach for the assessment of early on-therapy molecular responses and have important implications for the management of patients with SCLC, including the development of improved strategies for real-time tumor burden monitoring. See related commentary by Pellini and Chaudhuri, p. 2176.

Virus-like particle-based delivery of Cas9/guide RNA ribonucleoprotein efficiently edits the brachyury gene and inhibits chordoma growth in vivo

PURPOSE

Chordoma is a rare and aggressive bone cancer driven by the developmental transcription factor brachyury. Efforts to target brachyury are hampered by the absence of ligand-accessible small-molecule binding pockets. Genome editing with CRISPR systems provides an unprecedented opportunity to modulate undruggable transcription factor targets. However, delivery of CRISPR remains a bottleneck for in vivo therapy development. The aim was to investigate the in vivo therapeutic efficiency of Cas9/guide RNA (gRNA) ribonucleoprotein (RNP) delivery through a novel virus-like particle (VLP) by fusing an aptamer-binding protein to the lentiviral nucleocapsid protein.

METHODS

The p24 based ELISA and transmission electron microscopy were used to determine the characterization of engineered VLP-packaged Cas9/gRNA RNP. The deletion efficiency of brachyury gene in chordoma cells and tissues was measured by genome cleavage detection assay. RT-PCR, Western blot, immunofluorescence staining, and IHC were employed to test the function of brachyury deletion. Cell growth and tumor volume were measured to evaluate the therapeutic efficiency of brachyury deletion by VLP-packaged Cas9/gRNA RNP.

RESULTS

Our "all-in-one" VLP-based Cas9/gRNA RNP system allows for transient expression of Cas9 in chordoma cells, but maintains efficient editing capacity leading to approximately 85% knockdown of brachyury with subsequent inhibition of chordoma cell proliferation and tumor progression. In addition, this VLP-packaged brachyury-targeting Cas9 RNP avoids systemic toxicities in vivo.

CONCLUSION

Our preclinical studies demonstrate the potential of VLP-based Cas9/gRNA RNP gene therapy for the treatment of brachyury-dependent chordoma.

Liquid biopsy approaches to capture tumor evolution and clinical outcomes during cancer immunotherapy

Circulating cell-free tumor DNA (ctDNA) can serve as a real-time biomarker of tumor burden and provide unique insights into the evolving molecular landscape of cancers under the selective pressure of immunotherapy. Tracking the landscape of genomic alterations detected in ctDNA may reveal the clonal architecture of the metastatic cascade and thus improve our understanding of the molecular wiring of therapeutic responses. While liquid biopsies may provide a rapid and accurate evaluation of tumor burden dynamics during immunotherapy, the complexity of antitumor immune responses is not fully captured through single-feature ctDNA analyses. This underscores a need for integrative studies modeling the tumor and the immune compartment to understand the kinetics of tumor clearance in association with the quality of antitumor immune responses. Clinical applications of ctDNA testing in patients treated with immune checkpoint inhibitors have shown both predictive and prognostic value through the detection of genomic biomarkers, such as tumor mutational burden and microsatellite instability, as well as allowing for real-time monitoring of circulating tumor burden and the assessment of early on-therapy responses. These efforts highlight the emerging role of liquid biopsies in selecting patients for cancer immunotherapy, monitoring therapeutic efficacy, determining the optimal duration of treatment and ultimately guiding treatment selection and sequencing. The clinical translation of liquid biopsies is propelled by the increasing number of ctDNA-directed interventional clinical trials in the immuno-oncology space, signifying a critical step towards implementation of liquid biopsies in precision immuno-oncology.

Low-cost and clinically applicable copy number profiling using repeat DNA

BACKGROUND

Somatic copy number alterations (SCNAs) are an important class of genomic alteration in cancer. They are frequently observed in cancer samples, with studies showing that, on average, SCNAs affect 34% of a cancer cell's genome. Furthermore, SCNAs have been shown to be major drivers of tumour development and have been associated with response to therapy and prognosis. Large-scale cancer genome studies suggest that tumours are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Despite the frequency of SCNAs and their clinical relevance, the use of genomics assays in the clinic is biased towards targeted gene panels, which identify SNVs but provide limited scope to detect SCNAs throughout the genome. There is a need for a comparably low-cost and simple method for high-resolution SCNA profiling.

RESULTS

We present conliga, a fully probabilistic method that infers SCNA profiles from a low-cost, simple, and clinically-relevant assay (FAST-SeqS). When applied to 11 high-purity oesophageal adenocarcinoma samples, we obtain good agreement (Spearman's rank correlation coefficient, r_s=0.94) between conliga's inferred SCNA profiles using FAST-SeqS data (approximately £14 per sample) and those inferred by ASCAT using high-coverage WGS (gold-standard). We find that conliga outperforms CNVkit (r_s=0.89), also applied to FAST-SeqS data, and is comparable to QDNAseq (r_s=0.96) applied to low-coverage WGS, which is approximately four-fold more expensive, more laborious and less clinically-relevant. By performing an in silico dilution series experiment, we find that conliga is particularly suited to detecting SCNAs in low tumour purity samples. At two million reads per sample, conliga is able to detect SCNAs in all nine samples at 3% tumour purity and as low as 0.5% purity in one sample. Crucially, we show that conliga's hidden state information can be used to decide when a sample is abnormal or normal, whereas CNVkit and QDNAseq cannot provide this critical information.

CONCLUSIONS

We show that conliga provides high-resolution SCNA profiles using a convenient, low-cost assay. We believe conliga makes FAST-SeqS a more clinically valuable assay as well as a useful research tool, enabling inexpensive and fast copy number profiling of pre-malignant and cancer samples.

The Utility of Repetitive Cell-Free DNA in Cancer Liquid Biopsies

Liquid biopsy is a broad term that refers to the testing of body fluids for biomarkers that correlate with a pathological condition. While a variety of body-fluid components (e.g., circulating tumor cells, extracellular vesicles, RNA, proteins, and metabolites) are studied as potential liquid biopsy biomarkers, cell-free DNA (cfDNA) has attracted the most attention in recent years. The total cfDNA population in a typical biospecimen represents an immensely rich source of biological and pathological information and has demonstrated significant potential as a versatile biomarker in oncology, non-invasive prenatal testing, and transplant monitoring. As a significant portion of cfDNA is composed of repeat DNA sequences and some families (e.g., pericentric satellites) were recently shown to be overrepresented in cfDNA populations vs their genomic abundance, it holds great potential for developing liquid biopsy-based biomarkers for the early detection and management of patients with cancer. By outlining research that employed cell-free repeat DNA sequences, in particular the ALU and LINE-1 elements, we highlight the clinical potential of the repeat-element content of cfDNA as an underappreciated marker in the cancer liquid biopsy repertoire.

Response prediction and risk stratification of patients with rectal cancer after neoadjuvant therapy through an analysis of circulating tumour DNA

Background

Multiple approaches based on cell-free DNA (cfDNA) have been applied to detect minimal residual disease (MRD) and to predict prognosis or recurrence. However, a comparison of the approaches used in different cohorts and studies is difficult. We aimed to compare multiple approaches for MRD analysis after neoadjuvant therapy (NAT) in patients with locally advanced rectal cancer (LARC).

Methods

Sixty patients with LARC from a multicentre, phase II/III randomized trial were included, with tissue and blood samples collected. For each cfDNA sample, we profiled MRD using 3 approaches: personalized assay targeting tumour-informed mutations, universal panel of genes frequently mutated in colorectal cancer (CRC), and low depth sequencing for copy number alterations (CNAs).

Findings

Positive MRD based on post-NAT personalized assay was significantly associated with an increased risk of recurrence (HR = 27.38; log-rank P < 0.0001). MRD analysis based on universal panel (HR = 5.18; log-rank P = 0.00086) and CNAs analysis (HR = 9.24; log-rank P = 0.00017) showed a compromised performance in predicting recurrence. Both the personalized assay and universal panel showed complementary pattern to CNAs analysis in detecting cases with recurrence and the combination of the two types of biomarkers may lead to better performance.

Interpretation

The combination of mutation profiling and CNA profiling can improve the detection of MRD, which may help optimize the treatment strategies for patients with LARC.

Detection of malignant peripheral nerve sheath tumors in patients with neurofibromatosis using aneuploidy and mutation identification in plasma

Malignant peripheral nerve sheath tumors (MPNST) are the deadliest cancer that arises in individuals diagnosed with neurofibromatosis and account for nearly 5% of the 15,000 soft tissue sarcomas diagnosed in the United States each year. Comprised of neoplastic Schwann cells, primary risk factors for developing MPNST include existing plexiform neurofibromas (PN), prior radiotherapy treatment, and expansive germline mutations involving the entire NF1 gene and surrounding genes. PN develop in nearly 30–50% of patients with neurofibromatosis type 1 (NF1) and most often grow rapidly in the first decade of life. One of the most important aspects of clinical care for NF1 patients is monitoring PN for signs of malignant transformation to MPNST that occurs in 10–15% of patients. We perform aneuploidy analysis on ctDNA from 883 ostensibly healthy individuals and 28 patients with neurofibromas, including 7 patients with benign neurofibroma, 9 patients with PN and 12 patients with MPNST. Overall sensitivity for detecting MPNST using genome wide aneuploidy scoring was 33%, and analysis of sub-chromosomal copy number alterations (CNAs) improved sensitivity to 50% while retaining a high specificity of 97%. In addition, we performed mutation analysis on plasma cfDNA for a subset of patients and identified mutations in NF1, NF2, RB1, TP53BP2, and GOLGA2. Given the high throughput and relatively low sequencing coverage required by our assay, liquid biopsy represents a promising technology to identify incipient MPNST.

Liquid biopsies for residual disease and recurrence

Detection of minimal residual disease in patients with cancer, who are in complete remission with no cancer cells detectable, has the potential to improve recurrence-free survival through treatment selection. Studies analyzing circulating tumor DNA (ctDNA) in patients with solid tumors suggest the potential to accurately predict and detect relapse, enabling treatment strategies that may improve clinical outcomes. Over the past decade, assays for ctDNA detection in plasma samples have steadily increased in sensitivity and specificity. These are applied for the detection of residual disease after treatment and for earlier detection of recurrence. Novel clinical trials are now assessing how assays for "residual disease and recurrence" (RDR) may influence current treatment paradigms and potentially change the landscape of risk classification for cancer recurrence. In this review, we appraise the progress of RDR detection using ctDNA and consider the emerging role of liquid biopsy in the monitoring and management of solid tumors.

The unfolded protein response links tumor aneuploidy to local immune dysregulation

Aneuploidy is a chromosomal abnormality associated with poor prognosis in many cancer types. Here, we tested the hypothesis that the unfolded protein response (UPR) mechanistically links aneuploidy and local immune dysregulation. Using a single somatic copy number alteration (SCNA) score inclusive of whole‐chromosome, chromosome arm, and focal alterations in a pan‐cancer analysis of 9,375 samples in The Cancer Genome Atlas (TCGA) database, we found an inverse correlation with a cytotoxicity (CYT) score across disease stages. Co‐expression patterns of UPR genes changed substantially between SCNA^low and SCNA^high groups. Pathway activity scores showed increased activity of multiple branches of the UPR in response to aneuploidy. The PERK branch showed the strongest association with a reduced CYT score. The conditioned medium of aneuploid cells transmitted XBP1 splicing and caused IL‐6 and arginase 1 transcription in receiver bone marrow‐derived macrophages and markedly diminished the production of IFN‐γ and granzyme B in activated human T cells. We propose the UPR as a mechanistic link between aneuploidy and immune dysregulation in the tumor microenvironment.

Pembrolizumab for patients with leptomeningeal metastasis from solid tumors: efficacy, safety, and cerebrospinal fluid biomarkers

Background

The benefit of immune checkpoint inhibitors (ICIs) in patients with leptomeningeal metastases (LMM) is unknown.

Methods

We undertook a phase II trial of pembrolizumab in patients with LMM from solid tumors. Eligible patients had radiologic/cytologic LMM and Eastern Cooperative Oncology Group performance status 0–1. Pembrolizumab was administered intravenously at 200 mg q3W until disease progression/unacceptable toxicity. The primary endpoint was central nervous system (CNS) response after four cycles, defined radiologically/cytologically/clinically. Serial cerebrospinal fluid (CSF) was assessed for tumor-derived DNA (t-DNA) aneuploidy and cytokines.

Results

Thirteen of a planned 16 patients were treated between April 2017 and December 2019. The study closed early for poor accrual. Median age was 57 years (range: 22–79). Sixty-two percent of patients had tumors not traditionally ICI-responsive (hormone-receptor (HR)-positive breast carcinoma=39%; high-grade glioma=23%), while 38% had ICI-responsive tumors (non-small cell lung cancer (NSCLC)=23%, head and neck carcinoma=8%, cutaneous squamous carcinoma (CSC)=8%). CNS response was observed in 38% of patients at 12 weeks (95% CI 13.9% to 68.4%) by pre-defined criteria and LM-RANO, and 2 achieved durable complete responses (CSC=1, overall survival (OS) 3+ years; NSCLC=1, OS 9 months). Median CNS progression-free survival and OS was 2.9 months (95% CI 1.3 to NR) and 4.9 months (95% CI 3.7 to NR), respectively. Grade 3+ treatment-related adverse events occurred in 15% of patients. Sensitivity for LMM detection by t-DNA and cytopathology was 84.6% (95% CI 54.6% to 98.1%) and 53.9% (95% CI 25.1% to 80.8%), respectively. Pre-therapy and on-therapy CSF cytokine analysis demonstrated complete responders clustered together.

Conclusions

Pembrolizumab conferred a 38% CNS response rate in patients with LMM, a tolerable safety profile, and deep responses in selected patients with ICI-responsive tumors. CSF t-DNA may be sensitive for LMM detection, and immunologic subsets of CNS response warrant further study.

Trial registration number

NCT03091478

cfDNA Sequencing: Technological Approaches and Bioinformatic Issues

In the era of precision medicine, it is crucial to identify molecular alterations that will guide the therapeutic management of patients. In this context, circulating tumoral DNA (ctDNA) released by the tumor in body fluids, like blood, and carrying its molecular characteristics is becoming a powerful biomarker for non-invasive detection and monitoring of cancer. Major recent technological advances, especially in terms of sequencing, have made possible its analysis, the challenge still being its reliable early detection. Different parameters, from the pre-analytical phase to the choice of sequencing technology and bioinformatic tools can influence the sensitivity of ctDNA detection.

Massively Parallel Sequencing of Esophageal Brushings Enables an Aneuploidy-Based Classification of Patients With Barrett's Esophagus

BACKGROUND & AIMS

Aneuploidy has been proposed as a tool to assess progression in patients with Barrett's esophagus (BE), but has heretofore required multiple biopsies. We assessed whether a single esophageal brushing that widely sampled the esophagus could be combined with massively parallel sequencing to characterize aneuploidy and identify patients with disease progression to dysplasia or cancer.

METHODS

Esophageal brushings were obtained from patients without BE, with non-dysplastic BE (NDBE), low-grade dysplasia (LGD), high-grade dysplasia (HGD), or adenocarcinoma (EAC). To assess aneuploidy, we used RealSeqS, a technique that uses a single primer pair to interrogate ∼350,000 genome-spanning regions and identify specific chromosome arm alterations. A classifier to distinguish NDBE from EAC was trained on results from 79 patients. An independent validation cohort of 268 subjects was used to test the classifier at distinguishing patients at successive phases of BE progression.

RESULTS

Aneuploidy progression was associated with gains of 1q, 12p, and 20q and losses on 9p and 17p. The entire chromosome 8q was often gained in NDBE, whereas focal gain of 8q24 was identified only when there was dysplasia. Among validation subjects, a classifier incorporating these features with a global measure of aneuploidy scored positive in 96% of EAC, 68% of HGD, but only 7% of NDBE.

CONCLUSIONS

RealSeqS analysis of esophageal brushings provides a practical and sensitive method to determine aneuploidy in BE patients. It identifies specific chromosome changes that occur early in NDBE and others that occur late and mark progression to dysplasia. The clinical implications of this approach can now be tested in prospective trials.

Targeting loss of heterozygosity for cancer-specific immunotherapy

Developing therapeutic agents with potent antitumor activity that spare normal tissues remains a significant challenge. Clonal loss of heterozygosity (LOH) is a widespread and irreversible genetic alteration that is exquisitely specific to cancer cells. We hypothesized that LOH events can be therapeutically targeted by "inverting" the loss of an allele in cancer cells into an activating signal. Here we describe a proof-of-concept approach utilizing engineered T cells approximating NOT-gate Boolean logic to target counterexpressed antigens resulting from LOH events in cancer. The NOT gate comprises a chimeric antigen receptor (CAR) targeting the allele of human leukocyte antigen (HLA) that is retained in the cancer cells and an inhibitory CAR (iCAR) targeting the HLA allele that is lost in the cancer cells. We demonstrate that engineered T cells incorporating such NOT-gate logic can be activated in a genetically predictable manner in vitro and in mice to kill relevant cancer cells. This therapeutic approach, termed NASCAR (Neoplasm-targeting Allele-Sensing CAR), could, in theory, be extended to LOH of other polymorphic genes that result in altered cell surface antigens in cancers.

The mutational landscape of spinal chordomas and their sensitive detection using circulating tumor DNA

Background

Chordomas are the most common primary spinal column malignancy in the United States. The aim of this study was to determine whether chordomas may be detected by evaluating mutations in circulating tumor DNA (ctDNA).

Methods

Thirty-two patients with a biopsy-confirmed diagnosis of chordoma had blood drawn pre-operatively and/or at follow-up appointments. Mutations in the primary tumor were identified by whole exome sequencing and liquid biopsy by ddPCR and/or RACE-Seq was used to detect one or more of these mutations in plasma ctDNA at concurrent or later time points.

Results

At the time of initial blood draw, 87.1% of patients were ctDNA positive (P <.001). Follow-up blood draws in twenty of the patients suggest that ctDNA levels may reflect the clinical status of the disease. Patients with positive ctDNA levels were more likely to have greater mutant allele frequencies in their primary tumors (P = .004) and undergo radiotherapy (P = .02), and the presence of ctDNA may correlate with response to systemic chemotherapy and/or disease recurrence.

Conclusions

Detection of ctDNA mutations may allow for the detection and monitoring of disease progression for chordomas.

Clinical relevance of blood-based ctDNA analysis: mutation detection and beyond

Cell-free DNA (cfDNA) derived from tumours is present in the plasma of cancer patients. The majority of currently available studies on the use of this circulating tumour DNA (ctDNA) deal with the detection of mutations. The analysis of cfDNA is often discussed in the context of the noninvasive detection of mutations that lead to resistance mechanisms and therapeutic and disease monitoring in cancer patients. Indeed, substantial advances have been made in this area, with the development of methods that reach high sensitivity and can interrogate a large number of genes. Interestingly, however, cfDNA can also be used to analyse different features of DNA, such as methylation status, size fragment patterns, transcriptomics and viral load, which open new avenues for the analysis of liquid biopsy samples from cancer patients. This review will focus on the new perspectives and challenges of cfDNA analysis from mutation detection in patients with solid malignancies.

The genetics of ductal adenocarcinoma of the pancreas in the year 2020: dramatic progress, but far to go

The publication of the "Pan-Cancer Atlas" by the Pan-Cancer Analysis of Whole Genomes Consortium, a partnership formed by The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), provides a wonderful opportunity to reflect on where we stand in our understanding of the genetics of pancreatic cancer, as well as on the opportunities to translate this understanding to patient care. From germline variants that predispose to the development of pancreatic cancer, to somatic mutations that are therapeutically targetable, genetics is now providing hope, where there once was no hope, for those diagnosed with pancreatic cancer.

Detection and Diagnostic Utilization of Cellular and Cell-Free Tumor DNA

Because cancer is caused by an accumulation of genetic mutations, mutant DNA released by tumors can be used as a highly specific biomarker for cancer. Although this principle was described decades ago, the advent and falling costs of next-generation sequencing have made the use of tumor DNA as a biomarker increasingly practical. This review surveys the use of cellular and cell-free DNA for the detection of cancer, with a focus on recent technological developments and applications to solid tumors. It covers (a) key principles and technology enabling the highly sensitive detection of tumor DNA; (b) assessment of tumor DNA in plasma, including for genotyping, minimal residual disease detection, and early detection of localized cancer; (c) detection of tumor DNA in body cavity fluids, such as urine or cerebrospinal fluid; and (d) challenges posed to the use of tumor DNA as a biomarker by the phenomenon of benign clonal expansions.

Tumor DNA as a Cancer Biomarker through the Lens of Colorectal Neoplasia

Biomarkers have a wide range of applications in the clinical management of cancer, including screening and therapeutic management. Tumor DNA released from neoplastic cells has become a particularly active area of cancer biomarker development due to the critical role somatic alterations play in the pathophysiology of cancer and the ability to assess released tumor DNA in accessible clinical samples, in particular blood (i.e., liquid biopsy). Many of the early applications of tumor DNA as a biomarker were pioneered in colorectal cancer due to its well-defined genetics and common occurrence, the effectiveness of early detection, and the availability of effective therapeutic options. Herein, in the context of colorectal cancer, we describe how the intended clinical application dictates desired biomarker test performance, how features of tumor DNA provide unique challenges and opportunities for biomarker development, and conclude with specific examples of clinical application of tumor DNA as a biomarker with particular emphasis on early detection.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

A multimodality test to guide the management of patients with a pancreatic cyst

Pancreatic cysts are common and often pose a management dilemma, because some cysts are precancerous, whereas others have little risk of developing into invasive cancers. We used supervised machine learning techniques to develop a comprehensive test, CompCyst, to guide the management of patients with pancreatic cysts. The test is based on selected clinical features, imaging characteristics, and cyst fluid genetic and biochemical markers. Using data from 436 patients with pancreatic cysts, we trained CompCyst to classify patients as those who required surgery, those who should be routinely monitored, and those who did not require further surveillance. We then tested CompCyst in an independent cohort of 426 patients, with histopathology used as the gold standard. We found that clinical management informed by the CompCyst test was more accurate than the management dictated by conventional clinical and imaging criteria alone. Application of the CompCyst test would have spared surgery in more than half of the patients who underwent unnecessary resection of their cysts. CompCyst therefore has the potential to reduce the patient morbidity and economic costs associated with current standard-of-care pancreatic cyst management practices.

Current status of genetic urinary biomarkers for surveillance of non-muscle invasive bladder cancer: a systematic review

Background

Genetic biomarkers are a promising and growing field in the management of bladder cancer in all stages. The aim of this paper is to understand the role of genetic urinary biomarkers in the follow up of patients with non muscle invasive bladder cancer where there is increasing evidence that they can play a role in avoiding invasive techniques.

Methods

Following PRISMA criteria, we have performed a systematic review. The search yielded 164 unique articles, of which 21 articles were included involving a total of 7261 patients. Sixteen of the articles were DNA based biomarkers, analyzing different methylations, microsatellite aberrations and gene mutations. Five articles studied the role of RNA based biomarkers, based on measuring levels of different combinations of mRNA. QUADAS2 critical evaluation of each paper has been reported.

Results

There are not randomized control trials comparing any biomarker with the gold standard follow-up, and the level of evidence is 2B in almost all the studies. Negative predictive value varies between 55 and 98.5%, being superior in RNA based biomarkers.

Conclusions

Although cystoscopy and cytology are the gold standard for non muscle invasive bladder cancer surveillance, genetic urinary biomarkers are a promising tool to avoid invasive explorations to the patients with a safe profile of similar sensitivity and negative predictive value. The accuracy that genetic biomarkers can offer should be taken into account to modify the paradigm of surveillance in non muscle invasive bladder cancer patients, especially in high-risk ones where many invasive explorations are recommended and biomarkers experiment better results.

Machine learning-based genome-wide interrogation of somatic copy number aberrations in circulating tumor DNA for early detection of hepatocellular carcinoma

Background

DNAs released from tumor cells into blood (circulating tumor DNAs, ctDNAs) carry tumor-specific genomic aberrations, providing a non-invasive means for cancer detection. In this study, we aimed to leverage somatic copy number aberration (SCNA) in ctDNA to develop assays to detect early-stage HCCs.

Methods

We conducted low-depth whole-genome sequencing (WGS) to profile SCNAs in 384 plasma samples of hepatitis B virus (HBV)-related HCC and cancer-free HBV patients, using one discovery and two validation cohorts. To fully capture the robust signals of WGS data from the complete genome, we developed a machine learning-based statistical model that is focused on detection accuracy in early-stage HCC.

Findings

We built the model using a discovery cohort of 209 patients, achieving an overall area under curve (AUC) of 0.893, with 0.874 for early-stage (Barcelona clinical liver cancer [BCLC] stage 0-A) and 0.933 for advanced-stage (BCLC stage B-D). The performance of the model was then assessed in two validation cohorts (76 and 99 patients) that only consisted of patients with stage 0-A HCC. Our model exhibited a robust predictive performance, with an AUC of 0.920 and 0.812 for the two validation cohorts. Further analyses showed the impact of tumor sample heterogeneity in model training on detecting early-stage tumors, and a refined model addressing the heterogeneity in the discovery cohort significantly increased model performance in validation.

Interpretation

We developed an SCNA-based, machine learning-driven model in the non-invasive detection of early-stage HCC in HBV patients and demonstrated its performance through strict independent validations.

Measuring Performance Metrics of Machine Learning Algorithms for Detecting and Classifying Transposable Elements

Because of the promising results obtained by machine learning (ML) approaches in several fields, every day is more common, the utilization of ML to solve problems in bioinformatics. In genomics, a current issue is to detect and classify transposable elements (TEs) because of the tedious tasks involved in bioinformatics methods. Thus, ML was recently evaluated for TE datasets, demonstrating better results than bioinformatics applications. A crucial step for ML approaches is the selection of metrics that measure the realistic performance of algorithms. Each metric has specific characteristics and measures properties that may be different from the predicted results. Although the most commonly used way to compare measures is by using empirical analysis, a non-result-based methodology has been proposed, called measure invariance properties. These properties are calculated on the basis of whether a given measure changes its value under certain modifications in the confusion matrix, giving comparative parameters independent of the datasets. Measure invariance properties make metrics more or less informative, particularly on unbalanced, monomodal, or multimodal negative class datasets and for real or simulated datasets. Although several studies applied ML to detect and classify TEs, there are no works evaluating performance metrics in TE tasks. Here, we analyzed 26 different metrics utilized in binary, multiclass, and hierarchical classifications, through bibliographic sources, and their invariance properties. Then, we corroborated our findings utilizing freely available TE datasets and commonly used ML algorithms. Based on our analysis, the most suitable metrics for TE tasks must be stable, even using highly unbalanced datasets, multimodal negative class, and training datasets with errors or outliers. Based on these parameters, we conclude that the F1-score and the area under the precision-recall curve are the most informative metrics since they are calculated based on other metrics, providing insight into the development of an ML application.

Assessing aneuploidy with repetitive element sequencing

We report a sensitive PCR-based assay called Repetitive Element AneupLoidy Sequencing System (RealSeqS) that can detect aneuploidy in samples containing as little as 3 pg of DNA. Using a single primer pair, we amplified ∼350,000 amplicons distributed throughout the genome. Aneuploidy was detected in 49% of liquid biopsies from a total of 883 nonmetastatic, clinically detected cancers of the colorectum, esophagus, liver, lung, ovary, pancreas, breast, or stomach. Combining aneuploidy with somatic mutation detection and eight standard protein biomarkers yielded a median sensitivity of 80% in these eight cancer types, while only 1% of 812 healthy controls scored positive.

Establishment of a novel human cell line retaining the characteristics of the original pancreatic adenocarcinoma, and evaluation of MEK as a therapeutic target

Pancreatic cancer is a lethal solid malignancy with limited therapeutic options. The development of novel therapeutic drugs requires adequate new cell line models. A new pancreatic cancer cell line, designated PDXPC1, was established from one pancreatic ductal adenocarcinoma (PDAC) patient-derived xenograft. The PDXPC1 cells were stably cultured for >2 years and had a stable short tandem repeat profile. The PDXPC1 cell line retained the key mutations of the primary tumor, along with the epithelial origin and other important protein expression. The PDXPC1 cells induced rapid in vivo tumor growth, both subcutaneously and orthotopically, in a mouse model with an elevated CA199 level. The PDXPC1 cells showed weak growth, invasion and migration potency compared to another pancreatic cancer cell line, but were relatively resistant to multiple anti-cancer drugs. Interestingly, the MEK inhibitor trametinib significantly inhibited the proliferation of PDXPC1 cells, and not that of Panc-1 cells, by inactivating MEK/ERK/MYC signaling and activating the apoptotic pathway via Bcl-2 degradation. In conclusion, the PDXPC1 cell line, capturing the major characteristics of the primary tumor, may be a suitable tool for studying the underlying mechanisms of chemo-resistance in PDAC and developing new targeted therapeutic options.

Pathophysiology of ctDNA Release into the Circulation and Its Characteristics: What Is Important for Clinical Applications

The clinical implications of being able to accurately detect tumor-derived DNA in the circulation, termed circulating tumor DNA (ctDNA), could be enormous. Already, a plethora of clinical applications is under validation that include detection of minimal residual disease and predicting recurrence, monitoring response and resistance to treatment, identifying targets for therapies, and early detection. ctDNA is only a fraction of the total cell-free DNA (cfDNA) which confounds its detection and sometimes conceals its properties. To use ctDNA as a cancer biomarker with confidence, we need to understand its nature. Its characteristics, including size, half-life, and amount, are critical for the development of tests for its detection and discrimination from the rest of the cfDNA. Technological advances have enabled the detection and quantification of individual fragments of cfDNA, which is pivotal for clinical applications. Understanding the causes, the source of and the mechanisms of release of ctDNA are important for the interpretation of test results. Despite the many advances in understanding the nature and biology of ctDNA, we do not yet have a clear appreciation of the processes that govern its presence and levels in the circulation. ctDNA is not detectable in the blood of every cancer patient, and there is not a directly proportional relationship to tumor type, size, or stage. It is not clear if the lack of correlation with these specific clinical parameters is strictly due to technical or biological challenges. Better understanding of the pathophysiology of ctDNA is therefore important for the improvement of clinical applications and interpretation of their results.

A systematic review of the application of machine learning in the detection and classification of transposable elements

Background

Transposable elements (TEs) constitute the most common repeated sequences in eukaryotic genomes. Recent studies demonstrated their deep impact on species diversity, adaptation to the environment and diseases. Although there are many conventional bioinformatics algorithms for detecting and classifying TEs, none have achieved reliable results on different types of TEs. Machine learning (ML) techniques can automatically extract hidden patterns and novel information from labeled or non-labeled data and have been applied to solving several scientific problems.

Methodology

We followed the Systematic Literature Review (SLR) process, applying the six stages of the review protocol from it, but added a previous stage, which aims to detect the need for a review. Then search equations were formulated and executed in several literature databases. Relevant publications were scanned and used to extract evidence to answer research questions.

Results

Several ML approaches have already been tested on other bioinformatics problems with promising results, yet there are few algorithms and architectures available in literature focused specifically on TEs, despite representing the majority of the nuclear DNA of many organisms. Only 35 articles were found and categorized as relevant in TE or related fields.

Conclusions

ML is a powerful tool that can be used to address many problems. Although ML techniques have been used widely in other biological tasks, their utilization in TE analyses is still limited. Following the SLR, it was possible to notice that the use of ML for TE analyses (detection and classification) is an open problem, and this new field of research is growing in interest.

Evaluation of liquid from the Papanicolaou test and other liquid biopsies for the detection of endometrial and ovarian cancers

We report the detection of endometrial and ovarian cancers based on genetic analyses of DNA recovered from the fluids obtained during a routine Papanicolaou (Pap) test. The new test, called PapSEEK, incorporates assays for mutations in 18 genes as well as an assay for aneuploidy. In Pap brush samples from 382 endometrial cancer patients, 81% [95% confidence interval (CI), 77 to 85%] were positive, including 78% of patients with early-stage disease. The sensitivity in 245 ovarian cancer patients was 33% (95% CI, 27 to 39%), including 34% of patients with early-stage disease. In contrast, only 1.4% of 714 women without cancer had positive Pap brush samples (specificity, ~99%). Next, we showed that intrauterine sampling with a Tao brush increased the detection of malignancy over endocervical sampling with a Pap brush: 93% of 123 (95% CI, 87 to 97%) patients with endometrial cancer and 45% of 51 (95% CI, 31 to 60%) patients with ovarian cancer were positive, whereas none of the samples from 125 women without cancer were positive (specificity, 100%). Finally, in 83 ovarian cancer patients in whom plasma was available, circulating tumor DNA was found in 43% of patients (95% CI, 33 to 55%). When plasma and Pap brush samples were both tested, the sensitivity for ovarian cancer increased to 63% (95% CI, 51 to 73%). These results demonstrate the potential of mutation-based diagnostics to detect gynecologic cancers at a stage when they are more likely to be curable.

Untargeted Assessment of Tumor Fractions in Plasma for Monitoring and Prognostication from Metastatic Breast Cancer Patients Undergoing Systemic Treatment

The aim of this study was to assess the prognostic and predictive value of an untargeted assessment of tumor fractions in the plasma of metastatic breast cancer patients and to compare circulating tumor DNA (ctDNA) with circulating tumor cells (CTC) and conventional tumor markers. In metastatic breast cancer patients (n = 29), tumor fractions in plasma were assessed using the untargeted mFAST-SeqS method from 127 serial blood samples. Resulting z-scores for the ctDNA were compared to tumor fractions established with the recently published ichorCNA algorithm and associated with the clinical outcome. We observed a close correlation between mFAST-SeqS z-scores and ichorCNA ctDNA quantifications. Patients with mFAST-SeqS z-scores above three (34.5%) showed significantly worse overall survival (p = 0.014) and progression-free survival (p = 0.018) compared to patients with lower values. Elevated z-score values were clearly associated with radiologically proven progression. The baseline CTC count, carcinoembryonic antigen (CEA), and cancer antigen (CA)15-5 had no prognostic impact on the outcome of patients in the analyzed cohort. This proof of principle study demonstrates the prognostic impact of ctDNA levels detected with mFAST-SeqS as a very fast and cost-effective means to assess the ctDNA fraction without prior knowledge of the genetic landscape of the tumor. Furthermore, mFAST-SeqS-based ctDNA levels provided an early means of measuring treatment response.

Detection of Solid Tumor Molecular Residual Disease (MRD) Using Circulating Tumor DNA (ctDNA)

Circulating tumor DNA (ctDNA) is a component of cell-free DNA that is shed by malignant tumors into the bloodstream and other bodily fluids. Levels of ctDNA are typically low, particularly in patients with localized disease, requiring highly sophisticated methods for detection and quantification. Multiple liquid biopsy methods have been developed for ctDNA analysis in solid tumor malignancies and are now enabling detection and assessment of earlier stages of disease, post-treatment molecular residual disease (MRD), resistance to targeted systemic therapy, and tumor mutational burden. Understanding ctDNA biology, mechanisms of release, and clearance and size characteristics, in conjunction with the application of molecular barcoding and targeted error correction, have increased the sensitivity and specificity of ctDNA detection techniques. Combinatorial approaches including integration of ctDNA data with circulating protein biomarkers may further improve assay sensitivity and broaden the scope of ctDNA applications. Circulating viral DNA may be utilized to monitor disease in some virally induced malignancies. In spite of increasingly accurate methods of ctDNA detection, results need to be interpreted with caution given that somatic mosaicisms such as clonal hematopoiesis of indeterminate potential (CHIP) may give rise to genetic variants in the bloodstream unrelated to solid tumors, and the limited concordance observed between different commercial platforms. Overall, highly precise ctDNA detection and quantification methods have the potential to transform clinical practice via non-invasive monitoring of solid tumor malignancies, residual disease detection at earlier timepoints than standard clinical and/or imaging surveillance, and treatment personalization based on real-time assessment of the tumor genomic landscape.

LINE-1 ORF-1p enhances the transcription factor activity of pregnenolone X receptor and promotes sorafenib resistance in hepatocellular carcinoma cells

Background

LINE-1 ORF-1p is encoded by the human pro-oncogene LINE-1. Our previous work showed that LINE-1 ORF-1p could enhance the resistance of hepatocellular carcinoma (HCC) cells to antitumor agents. However, the mechanisms involved in LINE-1 ORF-1p-mediated drug resistance remain largely unknown.

Materials and methods

The endogenous mRNA level of LINE-1 ORF-1p in clinical HCC specimens was examined using quantitative PCR (qPCR). The prognosis of HCC patients was assessed using time to progression and overall survival. The transcription factor activity of pregnenolone X receptor (PXR) was examined using luciferase gene reporter assays, qPCR, chromatin immunoprecipitation assays and cellular subfraction assays. Protein interaction between LINE-1 ORF-1p and PXR was detected by co-immunoprecipitation. The effect of LINE-1 ORF-1p on sorafenib resistance in HCC cells was studied using in vitro and in vivo models.

Results

A high level of LINE-1 ORF-1p in clinical specimens was related to poor prognosis in patients who received sorafenib treatment. LINE-1 ORF-1p increased the transcription factor activity of PXR by interacting with PXR and enhancing its cytoplasmic/nuclear translocation, and recruiting PXR to its downstream gene promoter, in turn enhancing the expression of the sorafenib resistance-related genes, CYP3A4 and mdr-1. LINE-1 ORF-1p enhanced the resistance to and clearance of sorafenib in HCC cells.

Conclusion

LINE-1 ORF-1p enhances the transcription factor activation of PXR and promotes the clearance of and resistance to sorafenib in HCC cells.

Non-invasive detection of urothelial cancer through the analysis of driver gene mutations and aneuploidy

Current non-invasive approaches for detection of urothelial cancers are suboptimal. We developed a test to detect urothelial neoplasms using DNA recovered from cells shed into urine. UroSEEK incorporates massive parallel sequencing assays for mutations in 11 genes and copy number changes on 39 chromosome arms. In 570 patients at risk for bladder cancer (BC), UroSEEK was positive in 83% of those who developed BC. Combined with cytology, UroSEEK detected 95% of patients who developed BC. Of 56 patients with upper tract urothelial cancer, 75% tested positive by UroSEEK, including 79% of those with non-invasive tumors. UroSEEK detected genetic abnormalities in 68% of urines obtained from BC patients under surveillance who demonstrated clinical evidence of recurrence. The advantages of UroSEEK over cytology were evident in low-grade BCs; UroSEEK detected 67% of cases whereas cytology detected none. These results establish the foundation for a new non-invasive approach for detection of urothelial cancer.